This book serves as an introduction to Theory of Mind (ToM) in AI and Cognitive Science. The book provides an in-depth walk-through of core concepts: what ToM is, how we model ToM, what the applications of ToM are, and its relevance to both AI and Cognitive researchers.With the purpose of bridging multiple disciplines, this book curates contributions from leaders in Multi-Agent and Language experts, as well as Cognitive and Computational Psychologists, providing the reader with a comprehensive view of ToM and its real-world applications. It establishes a shared vocabulary for discussing ToM in AI, bridging interdisciplinary knowledge to guide informed and ethical research.

Theory of Mind in Natural and Artificial Intelligence is also meant to be more than an introductory anthology. For active researchers, the book will serve as a reference point for learning about models and applications, for which they might not be aware. ToM is both a well-explored and uncharted field of research. The book presents current mapping and active research questions, aimed to provide researchers, junior and senior alike, with guidance and directions to explore the next frontiers of ToM.

Nitay Alon is a postdoctoral researcher at MIT, hosted by Joshua Tenenbaum, and a Rothschild Fellow. His research centres on adaptiveness in multi-agent systems and the role Theory of Mind plays in partially observed Bayesian games, especially mixed-motive multi-agent settings, exploring issues such as deception, scepticism, and overmentalizing.

 Joseph Barnby is an Associate Professor of Cognitive Computational Science and AI+ Senior Fellow at King's College London, and Senior Fellow at the Perron Institute at the University of Western Australia,Centre for AI and Machine Learning at Edith Cowan University, and a FENS-Kavli Scholar. Joe is the director of the Social Computation and Representation (SoCR) lab that seeks to understand how natural and artificially intelligent agents build and maintain causal maps of social environments in health and disorder.

Reuth Mirsky is an Assistant Professor in the Computer Science department and the Mechanical Engineering department at Tufts University. In her research, she seeks algorithms, behaviours, and frameworks that challenge current assumptions made for human-aware AI agents. Reuth is an active member of the AI and HRI research communities. Some of her recent roles are a Track Chair at AAAI and ICAPS, program chair for the symposium on Technological Advances in Human-Robot Interactions (TAHRI), a guest editor in Frontiers of Artificial Intelligence, JAAMAS, and THRI. She was elected for IJCAI 2025 Early Career Spotlight and AAAI 2025 New Faculty Highlights.

Stefan Sarkadi is an Associate Professor in AI for Defence and Security and a Royal Academy of Engineering UK Intelligence Community Research Fellow at the University of Lincoln. He directs the Hybrid Intelligence and Deception Exploration (HIDE) Lab and co‑leads the Centre for AI in Defence and Security. He is internationally recognised for pioneering contributions to Deceptive AI, integrating insights from computer science, philosophy, cognitive science, and intelligence analysis. A central thread of his work is the development of deceptive AI agents with Theory of Mind capabilities. He also founded and chaired a series of international Workshops at AAAI, ECAI, and IJCAI and serves as Guest Editor for the JAAMAS.